---
title: "Correlation between Education (2014) and Income Datasets(2011-15) of TN"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    social: menu
    source_code: embed
    vertical_layout: fill
---

 

```{r setup, include=FALSE}
library(flexdashboard)
library("MASS")
library("dplyr")
library("ggplot2")
library("grid")
library("stringr")
library("reshape2")
library("plotly")
library("dygraphs")
library("metricsgraphics")
library("DT")
```

Column {data-width=750,data-height=750}
-----------------------------------------------------------------------

### Core Region Wise Vs Various Indicators

[tn_map link](https://hit.health.tn.gov/tnmap/print_tnmap.htm)
```{r}
education_df_plus_3 <- readRDS('./r-objects/education_df_plus_3.rds')
core_region_act <- education_df_plus_3 %>% 
   group_by(CORE_region) %>% 
   summarize(
     avg_act_scores =mean(ACT_Composite),
     avg_pupil_exp_times_thousand = mean(Per_Pupil_Expenditures)/1000,
     avg_graduation_rate = mean(Graduation),
     avg_suspension_rate = mean(Pct_Suspended),
     avg_dropout_rate = mean(Dropout),
     avg_hispanic= mean(Pct_Hispanic),
     avg_black = mean(Pct_Black),
     avg_native_american = mean(Pct_Native_American)
     ) %>% 
   ungroup() %>% 
   select(CORE_region,avg_act_scores,avg_pupil_exp_times_thousand,avg_graduation_rate,avg_suspension_rate,avg_dropout_rate,avg_hispanic,avg_black,avg_native_american) %>% 
  arrange(desc(avg_act_scores)) 

 
melt_core <- melt(data=core_region_act,id.vars ="CORE_region")

p1 <- ggplot(data=melt_core,aes(x=CORE_region,y=value,color=variable)) +
  geom_point() +
  geom_smooth(method='lm')  + 
  scale_size_continuous(range = c(5,12))
  

ggplotly(p1)

```

### Data Table


```{r}
mean_pupil_exp_vs_core_region <- education_df_plus_3 %>% 
  group_by(CORE_region) %>% 
  summarise(
    mean_pupil_exp = round(mean(Per_Pupil_Expenditures),2)
  ) %>% 
  ungroup() %>% 
  select(CORE_region,mean_pupil_exp) %>% 
  arrange(desc(mean_pupil_exp))


datatable(mean_pupil_exp_vs_core_region, options = list(
  searching = FALSE,
  pageLength = 5,
  lengthMenu = c(5, 10, 15, 20)
    ) 
)
```

Column {data-width=350}
-----------------------------------------------------------------------

### Number Of Tax Payers Over Years[Per Pupil Expenditure is highest in Davidson county/then Shelby]

```{r}
irs_2011_2015 <- readRDS('./r-objects/irs_2011_2015.rds')
ggplot_num_returns <- function(df, range, y.label="", point=FALSE) {
  df_sort_1 <- irs_2011_2015 %>% 
    dplyr::filter(sum_total_income_returns >= range) %>% 
    dplyr::select(
      county, year, sum_total_income_returns
    )
  
  p <- df_sort_1 %>% 
    ggplot(
      aes(
        x = year,
        y = sum_total_income_returns, 
        group = county,
        color = county
      )
    ) + 
    geom_line(size = 1.5) + 
    labs(y = y.label, x = "") +
    theme(axis.text.x = element_text(
        face = 'bold', 
        size = 10
      )
    ) +
    theme(axis.text.y = element_text(
        face = 'bold', 
        size = 10
      )
    ) +
    theme(axis.title.y = element_text(
        size = 10
      )
    ) +
    scale_y_continuous(labels = scales::comma) +
    scale_color_hue(l = 60, c = 50)
  
  if (point) {
    p + 
      geom_point() +
      geom_label(
        aes(label=sum_total_income_returns), 
        hjust = 0, 
        vjust = 0,
        nudge_x = -.5,
        nudge_y = .2
      )
  } else {
    p
  }
}
p1 <- ggplot_num_returns(irs_2011_2015, 20000, y.label = "Num of Tax Payers Per Year")

ggplotly(p1)


```

### Graduation Rate

```{r}

grad_rate1 <- paste0(round(max(education_df_plus_3$Graduation),2)," %")
valueBox(grad_rate1, caption = "Graduation Rate in Meigs County,TN (Southeast CORE)", icon = "fa-graduation-cap", color = "blue", href = NULL)

```

### ACT Scores

```{r}
act_score <- paste0(round(max(education_df_plus_3$ACT_Composite)))

valueBox(act_score, caption = "Avg 2014 ACT Scores in Williamson County,TN (Mid Cumberland CORE Region)  ", icon = "fa-thumbs-up", color = "green", href = NULL)

```

### Suspension Rate

```{r}
dropout_rate <- paste0(round(max(education_df_plus_3$Dropout),2), " %")

valueBox(dropout_rate, caption = "Drop Out Rate in Shelby County,TN(Southwest/Memphis CORE Region)", icon = "fa-thumbs-down", color = "red", href = NULL)


```